Multi-mode region-of-interest video object segmentation

• US 20070183661A1
• Filed: 02/07/2006
• Published: 08/09/2007
• Est. Priority Date: 02/07/2006
• Status: Active Grant

• Current Assignee: Qualcomm, Inc.
• Original Assignee: Qualcomm, Inc.
• Inventors: Wang, Haohong, El-Maleh, Khaled
• Granted Patent: US 8,150,155 B2
• Time in Patent Office: Days
• US Class Current: 382/173
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/20036 Morphological image processing
• CPC Class Codes: G06T 2207/20132 Image cropping
• CPC Class Codes: G06T 2207/30201 Face
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/174 involving the use of two or more images
• CPC Class Codes: G06T 7/194 involving foreground-background segmentation
• CPC Class Codes: G06T 7/215 Motion-based segmentation
• CPC Class Codes: G06V 10/25 Determination of region of interest [ROI] or a volume of interest [VOI]
• CPC Class Codes: G06V 40/162 using pixel segmentation or colour matching
• CPC Class Codes: G06V 40/165 using facial parts and geometric relationships
• CPC Class Codes: G06V 40/167 using comparisons between temporally consecutive images

Abstract

The disclosure is directed to techniques for automatic segmentation of a region-of-interest (ROI) video object from a video sequence. ROI object segmentation enables selected ROI or “foreground” objects of a video sequence that may be of interest to a viewer to be extracted from non-ROI or “background” areas of the video sequence. Examples of a ROI object are a human face or a head and shoulder area of a human body. The disclosed techniques include a hybrid technique that combines ROI feature detection, region segmentation, and background subtraction. In this way, the disclosed techniques may provide accurate foreground object generation and low-complexity extraction of the foreground object from the video sequence. A ROI object segmentation system may implement the techniques described herein. In addition, ROI object segmentation may be useful in a wide range of multimedia applications that utilize video sequences, such as video telephony applications and video surveillance applications.

Claims

1. A method comprising:

receiving a video frame of a video sequence;

applying one or more segmentation mode decision factors to the video frame to select a segmentation mode from at least a first segmentation mode and a second segmentation mode;

segmenting a region of interest (ROI) object from the video frame without reference to motion information for the video frame when the first segmentation mode is selected; and

segmenting an ROI object from the video frame based on motion information for the video frame and a different video frame of the video sequence when the second segmentation mode is selected.

2. The method of claim 1, wherein the different video frame is a previous video frame in the video sequence.

3. The method of claim 1, wherein applying the one or more segmentation mode decision factors comprises determining a computational complexity of the video frame, and selecting the first segmentation mode when the computation complexity is above a pre-determined level.

4. The method of claim 3, wherein determining the computational complexity comprises determine a number of ROI features within the video frame.

5. The method of claim 1, wherein applying the one or more segmentation mode decision factors comprises determining a desired segmentation quality of the video frame from an end-user, and selecting the first segmentation mode when the desired segmentation quality is above a pre-determined level.

6. The method of claim 1, wherein applying the one or more segmentation mode decision factors comprises determining an amount of similarity between the video frame and the different video frame of the video sequence, and selecting the first segmentation mode when the amount of similarity is below a pre-determined level.

7. The method of claim 6, wherein determining the amount of similarity comprises comparing a first color histogram of the video frame with a second color histogram of the different video frame to determine an amount of similarity between the first and second color histograms.

8. The method of claim 1, wherein applying the one or more segmentation mode decision factors comprises determining an amount of motion activity between the video frame and the different video frame of the video sequence, and selecting the first segmentation mode when the amount of motion activity is above a pre-determined level.

9. The method of claim 8, wherein determining the amount of motion activity comprises comparing a first location of the ROI object within the video frame with a second location of the ROI object within the different video frame to determine an amount of movement between the first and second locations.

10. The method of claim 1, wherein the different video frame directly precedes the video frame of the video sequence, wherein applying the one or more segmentation mode decision factors comprises determining the segmentation mode used to segment the different video frame of the video sequence, and selecting the second segmentation mode when the different video frame was segmented in the first segmentation mode.

11. The method of claim 1, wherein applying the one or more segmentation mode decision factors comprises determining a number of consecutive video frames of the video sequence that were segmented in the second segmentation mode, and selecting the first segmentation mode when the number of consecutive second segmentation mode video frames is above a pre-determined level.

12. A computer-readable medium comprising instructions that cause the programmable processor to:

receive a video frame of a video sequence;

apply one or more segmentation mode decision factors to the video frame to select a segmentation mode from at least a first segmentation mode and a second segmentation mode;

segment a region of interest (ROI) object from the video frame without reference to motion information for the video frame when the first segmentation mode is selected; and

segment an ROI object from the video frame based on motion information for the video frame and a different video frame of the video sequence when the second segmentation mode is selected.

13. The computer-readable medium of claim 12, wherein the instructions cause the programmable processor to determine a computational complexity of the video frame, and select the first segmentation mode when the computation complexity is above a pre-determined level.

14. The computer-readable medium of claim 13, wherein the instructions cause the programmable processor to determine a number of ROI features within the video frame.

15. The computer-readable medium of claim 12, wherein the instructions cause the programmable processor to determine a desired segmentation quality of the video frame from an end-user, and select the first segmentation mode when the desired segmentation quality is above a pre-determined level.

16. The computer-readable medium of claim 12, wherein the instructions cause the programmable processor to determine an amount of similarity between the video frame and the different video frame of the video sequence, and select the first segmentation mode when the amount of similarity is below a pre-determined level.

17. The computer-readable medium of claim 16, wherein the instructions cause the programmable processor to compare a first color histogram of the video frame with a second color histogram of the different video frame to determine an amount of similarity between the first and second color histograms.

18. The computer-readable medium of claim 12, wherein the instructions cause the programmable processor to determine an amount of motion activity between the video frame and the different video frame of the video sequence, and select the first segmentation mode when the amount of motion activity is above a pre-determined level.

19. The computer-readable medium of claim 18, wherein the instructions cause the programmable processor to compare a first location of the ROI object within the video frame with a second location of the ROI object within the different video frame to determine an amount of movement between the first and second locations.

20. The computer-readable medium of claim 12, wherein the different video frame directly precedes the video frame of the video sequence, wherein the instructions cause the programmable processor to determine the segmentation mode used to segment the different video frame of the video sequence, and select the second segmentation mode when the different video frame was segmented in the first segmentation mode.

21. The computer-readable medium of claim 12, wherein the instructions cause the programmable processor to determine a number of consecutive video frames of the video sequence that were segmented in the second segmentation mode prior to the video frame, and select the first segmentation mode when the number of consecutive second segmentation mode video frames is above a pre-determined level.

22. A video encoding device including a processor programmed to:

receive a video frame of a video sequence;

apply one or more segmentation mode decision factors to the video frame to select a segmentation mode from at least a first segmentation mode and a second segmentation mode;

segment a region of interest (ROI) object from the video frame without reference to motion information for the video frame when the first segmentation mode is selected; and

segment an ROI object from the video frame based on motion information for the video frame and a different video frame of the video sequence when the second segmentation mode is selected.

23. The device of claim 22, wherein the processor determines a computational complexity of the video frame, and selects the first segmentation mode when the computation complexity is above a pre-determined level.

24. The computer-readable medium of claim 23, wherein the processor determines a number of ROI features within the video frame.

25. The device of claim 22, wherein the processor determines a desired segmentation quality of the video frame from an end-user, and selects the first segmentation mode when the desired segmentation quality is above a pre-determined level.

26. The device of claim 22, wherein the processor determines an amount of similarity between the video frame and the different video frame of the video sequence, and selects the first segmentation mode when the amount of similarity is below a pre-determined level.

27. The device of claim 26, wherein the processor compares a first color histogram of the video frame with a second color histogram of the different video frame to determine an amount of similarity between the first and second color histograms.

28. The device of claim 22, wherein the processor determines an amount of motion activity between the video frame and the different video frame of the video sequence, and selects the first segmentation mode when the amount of motion activity is above a pre-determined level.

29. The device of claim 28, wherein the processor compares a first location of the ROI object within the video frame with a second location of the ROI object within the different video frame to determine an amount of movement between the first and second locations.

30. The device of claim 22, wherein the different video frame directly precedes the video frame of the video sequence, and wherein the processor determines the segmentation mode used to segment the different video frame of the video sequence, and selects the second segmentation mode when the different video frame was segmented in the first segmentation mode.

31. The device of claim 22, wherein the processor determines a number of consecutive video frames of the video sequence that were segmented in the second segmentation mode prior to the video frame, and selects the first segmentation mode when the number of consecutive second segmentation mode video frames is above a pre-determined level.